The dask.distributed progress bar differs from the ProgressBar used for
local diagnostics.
The progress function takes a Dask object that is executing in the background.

# Single machine progress barfromdask.diagnosicsimportProgressBarwithProgressBar():x.compute()# Distributed scheduler ProgressBarfromdask.distributedimportClient,progressclient=Client()# use dask.distributed by defaultx=x.persist()# start computation in the backgroundprogress(x)# watch progressx.compute()# convert to final result when done if desired

It is typically served at http://localhost:8787/status ,
but may be served elsewhere if this port is taken.
The address of the dashboard will be displayed if you are in a Jupyter Notebook.

There are numerous pages with information about task runtimes, communication,
statistical profiling, load balancing, memory use, and much more.
For more information we recommend the following video guide: